A Comprehensive Nontarget Analysis for the Molecular Reconstruction of Organic Aerosol Composition from Glacier Ice Cores

Aerosolomics based approach to discover source molecular markers: A case study for discriminating residential wood heating vs garden green waste burning emission sources

Biomass burning is a significant source of particulate matter (PM) in ambient air and its accurate source apportionment is a major concern for air quality. The discrimination between residential wood heating (RWH) and garden green waste burning (GWB) particulate matter (PM) is rarely achieved. The objective of this work was to evaluate the potential of non-targeted screening (NTS) analyses using HRMS (high resolution mass spectrometry) data to reveal discriminating potential molecular markers of both sources. Two residential wood combustion appliances (wood log stove and fireplace) were tested under different output conditions and wood moisture content. GWB experiments were carried out using two burning materials (fallen leaves and hedge trimming). PM samples were characterized using NTS approaches with both LC- and GC-HRMS (liquid and gas chromatography-HRMS). The analytical procedures were optimized to detect as many species as possible. Chemical fingerprints obtained were compared combining several multivariate statistical analyses (PCA, HCA and PLS-DA). Results showed a strong impact of the fuel nature and the combustion quality on the chemical fingerprints. 31 and 4 possible markers were discovered as characteristic of GWB and RWH, respectively. Complementary work was attempted to identify potential molecular formulas of the different potential marker candidates. The combination of HRMS NTS chemical characterization with multivariate statistical analyses shows promise for uncovering organic aerosol fingerprinting and discovering potential PM source markers.

Hybrid Targeted/Untargeted Screening Method for the Determination of Wildfire and Water-Soluble Organic Tracers in Ice Cores and Snow

Wildfires can influence the earth's radiative forcing through the emission of biomass-burning aerosols. To better constrain the impacts of wildfires on climate and understand their evolution under future climate scenarios, reconstructing their chemical nature, assessing their past variability, and evaluating their influence on the atmospheric composition are essential. Ice cores are unique to perform such reconstructions representing archives not only of past biomass-burning events but also of concurrent climate and environmental changes. Here, we present a novel methodology for the quantification of five biomass-burning proxies (syringic acid, vanillic acid, vanillin, syringaldehyde, and p-hydroxybenzoic acid) and one biogenic emission proxy (pinic acid) using solid phase extraction (SPE) and ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry. This method was also optimized for untargeted screening analysis to gain a broader knowledge about the chemical composition of organic aerosols in ice and snow samples. The method provides low detection limits (0.003-0.012 ng g^-1), high recoveries (74 ± 10%), and excellent reproducibility, allowing the quantification of the six proxies and the identification of 313 different molecules, mainly constituted by carbon, hydrogen, and oxygen. The effectiveness of two different sample storage strategies, i.e., re-freezing of previously molten ice samples and freezing of previously loaded SPE cartridges, was also assessed, showing that the latter approach provides more reproducible results.

How Low Can You Go? Selecting Intensity Thresholds for Untargeted Metabolomics Data Preprocessing

Untargeted mass spectrometry (MS) metabolomics is an increasingly popular approach for characterizing complex mixtures. Recent studies have highlighted the impact of data preprocessing for determining the quality of metabolomics data analysis. The first step in data processing with untargeted metabolomics requires that signal thresholds be selected for which features (detected ions) are included in the dataset. Analysts face the challenge of knowing where to set these thresholds; setting them too high could mean missing relevant features, but setting them too low could result in a complex and unwieldy dataset. This study compared data interpretation for an example metabolomics dataset when intensity thresholds were set at a range of feature heights. The main observations were that low signal thresholds (1) improved the limit of detection, (2) increased the number of features detected with an associated isotope pattern and/or an MS-MS fragmentation spectrum, and (3) increased the number of in-source clusters and fragments detected for known analytes of interest. When the settings of parameters differing in intensities were applied on a set of 39 samples to discriminate the samples through principal component analyses (PCA), similar results were obtained with both low- and high-intensity thresholds. We conclude that the most information-rich datasets can be obtained by setting low-intensity thresholds. However, in the cases where only a qualitative comparison of samples with PCA is to be performed, it may be sufficient to set high thresholds and thereby reduce the complexity of the data processing and amount of computational time required.

Anthropogenic and Biogenic Contributions to the Organic Composition of Coastal Submicron Sea Spray Aerosol

The organic composition of coastal sea spray aerosol is important for both atmospheric chemistry and public health but remains poorly characterized. Coastal waters contain an organic material derived from both anthropogenic processes, such as wastewater discharge, and biological processes, including biological blooms. Here, we probe the chemical composition of the organic fraction of sea spray aerosol over the course of the 2019 SeaSCAPE mesocosm experiment, in which a phytoplankton bloom was facilitated in natural coastal water from La Jolla, California. We apply untargeted two-dimensional gas chromatography to characterize submicron nascent sea spray aerosol samples, reporting ∼750 unique organic species traced over a 19 day phytoplankton bloom experiment. Categorization and quantitative compositional analysis reveal three major findings. First, anthropogenic species made up 30% of total submicron nascent sea spray aerosol organic mass under the pre-bloom condition. Second, biological activity drove large changes within the aerosolized carbon pool, decreasing the anthropogenic mass fraction by 89% and increasing the biogenic and biologically transformed fraction by a factor of 5.6. Third, biogenic marine organics are underrepresented in mass spectral databases in comparison to marine organic pollutants, with more than twice as much biogenic aerosol mass attributable to unlisted compounds.

Nontarget Screening Exhibits a Seasonal Cycle of PM2.5 Organic Aerosol Composition in Beijing

The molecular composition of atmospheric particulate matter (PM) in the urban environment is complex, and it remains a challenge to identify its sources and formation pathways. Here, we report the seasonal variation of the molecular composition of organic aerosols (OA), based on 172 PM_2.5 filter samples collected in Beijing, China, from February 2018 to March 2019. We applied a hierarchical cluster analysis (HCA) on a large nontarget-screening data set and found a strong seasonal difference in the OA chemical composition. Molecular fingerprints of the major compound clusters exhibit a unique molecular pattern in the Van Krevelen-space. We found that summer OA in Beijing features a higher degree of oxidation and a higher proportion of organosulfates (OSs) in comparison to OA during wintertime, which exhibits a high contribution from (nitro-)aromatic compounds. OSs appeared with a high intensity in summer-haze conditions, indicating the importance of anthropogenic enhancement of secondary OA in summer Beijing. Furthermore, we quantified the contribution of the four main compound clusters to total OA using surrogate standards. With this approach, we are able to explain a small fraction of the OA (∼11-14%) monitored by the Time-of-Flight Aerosol Chemical Speciation Monitor (ToF-ACSM). However, we observe a strong correlation between the sum of the quantified clusters and OA measured by the ToF-ACSM, indicating that the identified clusters represent the major variability of OA seasonal cycles. This study highlights the potential of using nontarget screening in combination with HCA for gaining a better understanding of the molecular composition and the origin of OA in the urban environment.

Occurrence and in vitro toxicity of organic compounds in urban background PM2.5

This study describes the chemical composition and in vitro toxicity of the organic fraction of fine particulate matter (PM_2.5) at an urban background site, which receives emissions either from Frankfurt international airport or the city centre, respectively. We analysed the chemical composition of filter extracts (PM_2.5) using ultrahigh-performance liquid chromatography coupled to a high-resolution mass spectrometer, followed by a non-target analysis. In parallel, we applied the bulk of the filter extracts to a Microtox and acetylcholinesterase-inhibition assay for in vitro toxicity testing. We find that both the chemical composition and toxicity depend on the prevailing wind directions, and the airport operating condition, respectively. The occurrence of the airport marker compounds tricresyl phosphate and pentaerythritol esters depends on the time of the day, reflecting the night flight ban as well as an airport strike event during November 2019. We compared the organic aerosol composition and toxicity from the airport wind-sector against the city centre wind-sector. We find that urban background aerosol shows a higher baseline toxicity and acetylcholinesterase inhibition compared to rural PM_2.5 that is advected over the airport. Our results indicate that the concentration and individual composition of PM_2.5 influence the toxicity. Suspected drivers of the acetylcholinesterase inhibition are i.e. organophosphorus esters like triphenyl phosphate and cresyldiphenyl phosphate, and the non-ionic surfactant 4-tert-octylphenol ethoxylate. However, further research is necessary to unambiguously identify harmful organic air pollutants and their sources and quantify concentration levels at which adverse effects in humans and the environment can occur.

Towards comprehensive non-target screening using heart-cut two-dimensional liquid chromatography for the analysis of organic atmospheric tracers in ice cores

Non-target screening of secondary organic aerosol compounds in ice cores is used to reconstruct atmospheric conditions and sources and is a valuable tool to elucidate the chemical profiles of samples with the aim to obtain as much information as possible from one mass spectrometric measurement. The coupling of mass spectrometry to chromatography limits the results of a non-target screening to signals of compounds within a certain polarity range based on the utilized stationary phases of the columns. Comprehensive two-dimensional liquid chromatography (LCxLC) introduces a second column of different functionality to enable the analysis of a broader range of analytes. Conventional LCxLC requires complex instrumental setups and is difficult to implement for most laboratories. In this work we demonstrate an approach to approximate a comprehensive non-target screening using a simple instrumental setup employing two columns of orthogonal functionalities (HILIC and reversed-phase), an additional pump, and an additional six-port valve. The void volume of the first dimension is transferred to the reversed-phase column to analyze low-polarity compounds during the re-equilibration of the HILIC. Method validation showed adequate repeatability and detection limits for two selected void volume markers and application to snow samples collected at the high-alpine research station Jungfraujoch yielded a total of 270 signals. Comparison to the one-dimensional HILIC approach revealed 175 signals exclusively detected in the two-dimensional method, of which 23 were detected in the second dimension. Detailed analysis of the chemical composition showed consistency with expected compounds in snow samples like lignin or cellulose combustion products from biomass burning or secondary organic aerosol constituents. The results confirmed that one-dimensional chromatography was not sufficient to cover the entire range of compounds and the developed two-dimensional approach will improve the information content from non-target screening while maintaining time of analysis and a simple instrumental setup.